PhD Data Science Intern

Job Description

Data Scientist Intern (TikTok Shop Business Product DS) – 2026 Start (PhD) | TikTok

The Tone:
This is a PhD internship at TikTok, with start dates available in 2026. TikTok is the leading destination for short-form mobile video and operates a global e-commerce business. This role is crucial for leveraging rigorous data analysis and scientific methodologies to drive business growth, enhance operational efficiency, and improve the experience for users, merchants, and creators worldwide within the TikTok Shop ecosystem. The internship aims to provide students with the opportunity to actively contribute to TikTok’s products, research, and emerging technologies.

The TL;DR
• Role: Internship (PhD)
• Pay: $52.25 hourly
• Team: TikTok Global E-commerce Data Science team
• Mission: This person conducts rigorous data analysis and applies scientific methodologies to drive business growth, enhance operational efficiency, and improve user, merchant, and creator experiences within TikTok’s global e-commerce products.
• Tech Stack: SQL, Python, R, Scikit-learn, TensorFlow, PyTorch, Hive, Spark, Hadoop

What You’ll Actually Do
• Analysis: Conduct data analysis for TikTok’s global e-commerce products, covering areas such as creators & merchants, content e-commerce, promotion tools, shoptap, and transaction flow.
• Experimentation: Design and analyze A/B tests, evaluate product optimizations, analyze campaign performance, monitor key metric fluctuations, and assess client-side version updates.
• Optimization: Analyze country-specific factors influencing product optimization and business growth, and propose actionable product improvement solutions aligned with business direction.
• Collaboration: Collaborate closely with product managers, operations, engineering, and algorithm teams to implement data-driven strategies and deliver measurable business impact.
• Infrastructure: Build and maintain e-commerce product metric systems, working with data engineering teams to construct foundational data pipelines and visual dashboards, enabling business stakeholders to gain actionable insights.

The Must-Haves
• Background: Currently pursuing a PhD in Computer Science, Statistics, Econometrics, Mathematics, or other quantitative disciplines.
• Experience: Solid foundation in statistics, with hands-on experience in A/B testing, regression analysis, and causal inference.
• Skills: Proficient in data analysis tools and languages such as SQL, Python, or R; strong data visualization skills and ability to clearly communicate analytical insights through dashboards and reports.
• Bonus: Experience in cross-border or international e-commerce data analysis or modeling; familiarity with machine learning frameworks or predictive modeling, with hands-on experience using tools such as Scikit-learn, TensorFlow, or PyTorch; experience working with big data technologies such as Hive, Spark, or Hadoop; strong cross-functional communication skills.